• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.1-23
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• 2021

This study introduces novel research using Practice Context Models supported by Knowledge Networks and Percolation Theory with the aim to contribute to knowledge management in Proof-of-Concept (PoC) activities. The authors envision this proposal as a potential instrument to identify network structures based on a percolation (propagation) threshold and to analyze the importance of nodes (e.g., practitioners, practices, competencies, movements, and scenarios) during the percolation of knowledge in PoC activities. After thirty months immersed in the natural PoC habitat, acting as observers and practitioners, and supported by an ethnographic exercise and a designer-research mindset, the authors identified the production of meaning in PoC activities occurring in a hermeneutic circle characterized by the presence of several knowledge networks; thus, discovering the 'natural knowledge' in PoC as a spectrum of cognitive development spread throughout its network, as each node could produce and disseminate certain knowledge that flows and influences other nodes. Therefore, this research presents the use of Practice Context Models 'connected' to Knowledge Networks and Percolation Theory as a potential and feasible proposal to be built using the attribution of values (weights) to the nodes (e.g., practitioners, practices, competencies, movements, scenarios, and also knowledge) in the context of PoC with the aim to allow the players (e.g., PoC practitioners) to have more flexibility in building alliances with other players (new nodes); that is, focusing on those nodes with higher value (focus on quality) in collaboration networks, i.e., alliances (connections) with the aim to contribute to knowledge management in the context of PoC.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.125-144
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• 2022

When a variable message signs (VMS) system displays false information related to traffic safety caused by malicious attacks, it could pose a serious risk to drivers. If the normal message patterns displayed on the VMS system are learned, it would be possible to detect and respond to the anomalous messages quickly. This paper proposes a method for detecting anomalous messages by learning the normal patterns of messages using a bi-directional generative pre-trained transformer (GPT) network. In particular, the proposed method was trained using the normal messages and their system parameters to minimize the corresponding negative log-likelihood (NLL) values. After adequate training, the proposed method could detect an anomalous message when its NLL value was larger than a pre-specified threshold value. The experiment results showed that the proposed method could detect malicious messages and cases when the system error occurs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1853-1858
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• 2021

O-rings fill the gaps between mechanical parts. Until now, the sorting of defective products has been performed visually and manually, so classification errors often occur. Therefore, a camera-based defect classification system without human intervention is required. However, a binarization process is required to separate the required region from the background in the camera input image. In this paper, an adaptive binarization technique that considers the surrounding pixel values is applied to solve the problem that single-threshold binarization is difficult to apply due to factors such as changes in ambient lighting or reflections. In addition, the convex hull technique is also applied to compensate for the missing pixel part. And the learning model to be applied to the separated region applies the residual error-based deep learning neural network model, which is advantageous when the defective characteristic is non-linear. It is suggested that the proposed system through experiments can be applied to the automation of O-ring defect detection.

• Clinical and Experimental Pediatrics
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• v.64 no.12
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• pp.652-660
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• 2021

Background: Viral load and shedding duration are highly associated with the transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, limited studies have reported on viral load or shedding in children and adolescents infected with sudden acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Purpose: This study aimed to investigate the natural course of viral load in asymptomatic or mild pediatric cases. Methods: Thirty-one children (<18 years) with confirmed SARS-CoV-2 infection were hospitalized and enrolled in this study. Viral loads were evaluated in nasopharyngeal swab samples using real-time reverse transcription polymerase chain reaction (E, RdRp, N genes). cycle threshold (Ct) values were measured when patients met the clinical criteria to be released from quarantine. Results: The mean age of the patients was 9.8 years, 18 (58%) had mild disease, and 13 (42%) were asymptomatic. Most children were infected by adult family members, most commonly by their mothers. The most common symptoms were fever and sputum (26%), followed by cough and runny nose. Nine patients (29%) had a high or intermediate viral load (Ct value≤30) when they had no clinical symptoms. Viral load showed no difference between symptomatic and asymptomatic patients. Viral rebounds were found in 15 cases (48%), which contributed to prolonged viral detection. The mean duration of viral detection was 25.6 days. Viral loads were significantly lower in patients with viral rebounds than in those with no rebound (E, P=0.003; RdRp, P=0.01; N, P=0.02). Conclusion: Our study showed that many pediatric patients with coronavirus disease 2019 (COVID-19) experienced viral rebound and showed viral detection for more than 3 weeks. Further studies are needed to investigate the relationship between viral rebound and infectiousness in COVID-19.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.28 no.2
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• pp.1-6
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• 2022

Background: This study investigated the effects of Kinesio taping application on lower back pressure pain and balance ability among university students with chronic lower back pain. Methods: A total of thirty university students between 20 to 30 years of age with chronic lower back pain were divided randomly into two groups, the control and the experimental group. In the control group (n=15), placebo taping was applied to the lumbar region. In the experimental group (n=15), Kinesio taping was applied to the erector spine muscles of the lower back. The groups were assessed for lower back pressure pain and balance ability, before and after the taping application. Pain was measured by the pain pressure threshold (PPT), and balance was measured using the good balance system (GBS). Results: There were significant improvements in both the PPT and GBS of the Kinesio taping group compared to pre-treatment values (p<.05), while the placebo taping group showed no significant change (p>.05). In addition, the Kinesio taping group had a statistically significant difference in PPT and GBS compared to the placebo taping group (p<.05). Conclusion: The Kinesio taping application is more effective than the placebo taping application in the improvement of lower back pressure pain and balance ability among university students with chronic lower back pain.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.351-357
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• 2022

Purpose: Convolutional neural networks (CNNs) have rapidly emerged as one of the most promising artificial intelligence methods in the field of medical and dental research. CNNs can provide an effective diagnostic methodology allowing for the detection of early-staged diseases. Therefore, this study aimed to evaluate the performance of a deep CNN algorithm for apical lesion segmentation from panoramic radiographs. Materials and Methods: A total of 1000 panoramic images showing apical lesions were separated into training (n=800, 80%), validation (n=100, 10%), and test (n=100, 10%) datasets. The performance of identifying apical lesions was evaluated by calculating the precision, recall, and F1-score. Results: In the test group of 180 apical lesions, 147 lesions were segmented from panoramic radiographs with an intersection over union (IoU) threshold of 0.3. The F1-score values, as a measure of performance, were 0.828, 0.815, and 0.742, respectively, with IoU thresholds of 0.3, 0.4, and 0.5. Conclusion: This study showed the potential utility of a deep learning-guided approach for the segmentation of apical lesions. The deep CNN algorithm using U-Net demonstrated considerably high performance in detecting apical lesions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1759-1768
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• 2022

This paper proposes a model to detect depression-related emotions in a user's speech using wellness dialogue scripts provided by AI Hub, topic-specific daily conversation datasets, and chatbot datasets published on Github. There are 18 emotions, including depression and lethargy, in depression-related emotions, and emotion classification tasks are performed using KoBERT and KOELECTRA models that show high performance in language models. For model-specific performance comparisons, we build diverse datasets and compare classification results while adjusting batch sizes and learning rates for models that perform well. Furthermore, a person performs a multi-classification task by selecting all labels whose output values are higher than a specific threshold as the correct answer, in order to reflect feeling multiple emotions at the same time. The model with the best performance derived through this process is called the Depression model, and the model is then used to classify depression-related emotions for user utterances.

• Journal of Microbiology and Biotechnology
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• v.33 no.6
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• pp.753-759
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• 2023

The genus Paenibacillus contains a variety of biologically active compounds that have potential applications in a range of fields, including medicine, agriculture, and livestock, playing an important role in the health and economy of society. Our study focused on the bacterium SS4^T (KCTC 43402^T = GDMCC 1.3498^T), which was characterized using a polyphasic taxonomic approach. This strain was analyzed using antiSMASH, BAGEL4, and PRISM to predict the secondary metabolites. Lassopeptide clusters were found using all three analysis methods, with the possibility of secretion. Additionally, PRISM found three biosynthetic gene clusters (BGC) and predicted the structure of the product. Genome analysis indicated that glucoamylase is present in SS4^T. 16S rRNA sequence analysis showed that strain SS4^T most closely resembled Paenibacillus marchantiophytorum DSM 29850^T (98.22%), Paenibacillus nebraskensis JJ-59^T (98.19%), and Paenibacillus aceris KCTC 13870^T (98.08%). Analysis of the 16S rRNA gene sequences and Type Strain Genome Server (TYGS) analysis revealed that SS4^T belongs to the genus Paenibacillus based on the results of the phylogenetic analysis. As a result of the matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF/MS) results, SS4^T was determined to belong to the genus Paenibacillus. Comparing P. marchantiophytorum DSM 29850^T with average nucleotide identity (ANI 78.97%) and digital DNA-DNA hybridization (dDDH 23%) revealed values that were all less than the threshold for bacterial species differentiation. The results of this study suggest that strain SS4^T can be classified as a Paenibacillus andongensis species and is a novel member of the genus Paenibacillus.

• Animal Bioscience
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• v.36 no.9
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• pp.1414-1425
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• 2023

Objective: Long chain n-3 polyunsaturated fatty acids (PUFA) exert positive effects on human health. The long chain n-3 PUFA of pork can be increased by adding fish oil to the diet. Due to the cost and availability of fish oil an alternative source must be found. Methods: This study evaluated the effect of five dietary oils on meat quality, fatty acid composition and lipid stability. The five diets contained 1% palm oil (Control), 1% soya oil, 1% linseed oil, 1% fish oil, and 1% Echium oil, respectively. The trial consisted of 60 gilts, randomly allocated to five groups. Results: All color parameters, extractable fat content, fat free dry matter, and moisture content of the m. longissimus muscle were unaffected by dietary treatment. Consumers and a trained sensory panel could not detect a difference between the control samples and the Echium oil sample during sensory analysis. Samples containing higher levels of PUFA (soya, linseed, fish, and Echium oil) had higher levels of primary and secondary lipid oxidation products after refrigerated and frozen storage. However, these values were still well below the threshold value where off flavors can be detected. The Echium oil treatment had significantly higher levels of long chain PUFA than the linseed oil treatment, but it was still significantly lower than that of the fish oil treatment. Conclusion: Echium oil supplementation did not increase the levels of n-3 to the same extent as fish oil did. The result did however suggest that Echium oil can be used in pig diets to improve muscle long chain n-3 fatty acid content without any adverse effects on meat quality when compared to linseed, soya, and palm oil.

• Korean Journal of Environmental Agriculture
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• v.41 no.4
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• pp.261-275
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• 2022

BACKGROUND: Prior to implementing a positive list system (PLS), there is a need to establish acceptable daily intake (ADI) and maximum residue limit (MRL) for veterinary drugs that have been approved a few decades ago in South Korea. On top of that, chronic dietary exposure assessment of veterinary drug residues should be performed to determine whether the use of these veterinary drugs would cause health concerns or not. METHODS AND RESULTS: To establish the ADI, the relevant toxicological data were collected from evaluation reports issued by international organizations. A slightly modified global estimate of chronic dietary exposure (GECDE) model was employed in the exposure assessment owing to the limited residual data. Therefore, only the ADI of ephedrine was established due to insufficient data for the other veterinary drugs. Thus, instead of ADI, the threshold of toxicological concern (TTC) value was used for the other drugs. Lastly, the hazard index (HI) was calculated, except for etizazole hydrochloride, due to the potential of mutagenicity. CONCLUSION(S): The HI values of ephedrine, menichlopholan, and anacolin were found to be as high as 6.4%, suggesting that chronic dietary exposure to the residues from these uses was unlikely to be a public health concern. Further research for exposure assessment of veterinary drug residues should be performed using up-todate Korean national health and nutrition examination survey (KNHANES) food consumption data. In addition, all relevant available data sources should be utilized for identifying the potentials of toxicity.